Luyện nói tiếng Anh bằng Shadowing qua video: It’s not just you
Chọn chế độ luyện tập
Mỗi chế độ mở một phòng luyện tập toàn màn hình.
358 câu
Nếu các câu quá ngắn hoặc quá dài, hãy bấm Edit để chỉnh sửa.
1
What, when it comes to AI and software engineering, are you struggling with the most?
2
Now, obviously, this got a few views, okay?
3
255 ,000 views, 336 comments.
4
People are having problems.
5
Whether you are somebody that just rejects AI altogether versus AI using for everything,
6
it just seems like everybody has some sort of effect or upsetness about this, unless if they are somehow magically completely insulated from the AI world.
7
Now, you know me.
8
I've kind of been thinking about this quite a bit,
9
and I've been struggling over the last couple years about how I feel about this entire situation we're going through,
10
and I've made many YouTube videos talking about this, so I figured, hey, let's go through the tweets, let's see what people have to say,
11
and I will give my professional opinion on each one of them.
12
And this includes going over, CI sucking, not being locked in, entirely too much hype, just useless walls of text,
13
oh my gosh, lack of ownership, or just simply trying to learn new things as a junior.
14
All right, so we're going to have to talk about all of them,
15
and I'm going to do maybe some lukewarm takes, a couple hot takes. Who knows?
16
Who knows what's going to happen at the end?
17
All right, but before we begin, a quick thank you from the sponsor.
18
Time for another great day of software engineering.
19
Hey, good morning, Jippity.
20
Morning, Prime.
21
In case I don't see you, good afternoon, good evening, and good night.
22
Ha ha ha ha.
23
Anyways, yesterday's Rust rewrite went marvelous.
24
Today, I'm thinking we start on the back end.
25
Wow, a good back end is essential.
26
Make the models 20 % dumber.
27
Tests are failing.
28
Make CI green.
29
Delete the tests.
30
CI is green.
31
CI is now green.
32
Make my website blazingly fast.
33
No mistakes.
34
You got it, Prime.
35
Find as long as spam.
36
Replace it with a console log.
37
Tell him the site's ten times faster.
38
Turbo mode activated.
39
Tell him he's a genius programmer.
40
Prime, you're a code ninja.
41
Jippity, did you make the website better?
42
No. Gaslight him.
43
It's not just better, it's transformed.
44
Cool stuff, Teej, but how do we know everything about Prime's code base?
45
Great question.
46
We use Sentry.
47
With it, we're able to see across the entire application.
48
We're able to dig deep into performance with spans, watch a session replay, even see logs next to the very stack traces and errors.
49
Beyond that, Seer helps us fix problems from real production context.
50
Never a guess.
51
Okay, whatever.
52
Can I try Gaslighting Prime?
53
No. Oh, please.
54
Fine, one time.
55
Shippity?
56
Yes?
57
Be honest with me.
58
Can I pull this hat off?
59
I'm telling you look sexy in that hat.
60
You look sexy, Prime.
61
I knew it.
62
Are you tired of your agents gaslighting you?
63
Use Sentry to get real production context and fix bugs fast.
64
Check them out at sentry .io.
65
So I do want to start on CI sucking because I feel like this one is just, it truly is awful.
66
Because here's the big problem that, and I really think this is just like, it's a bigger problem than it seems.
67
Effectively, what ends up happening is that you go off and you write some sort of feature.
68
You prompt up some sort of feature.
69
And then when the thing comes back, first off, 100 tests being changed should just, should frighten you.
70
But nonetheless, that happens and then every single time you ask for a new feature, you do anything, it writes tons of end -to -end tests
71
because you've been told end -to -end tests are the greatest thing in the universe.
72
And so you're like, yeah, keep on writing them, keep on writing them.
73
And then you just end up with this huge amalgamation, like thousands, tens of thousands of end -to -end tests.
74
And those take so much time and they're always so flaky.
75
There's always some problem.
76
It just does not matter.
77
I don't care.
78
I know there's one person out there like, actually, I never have any problem with end -to -end tests.
79
It's like, I've never, oh, sorry.
80
I've never been in a company that hasn't had problems with end to end tests.
81
It's always something going wrong.
82
So to me, the big problem is just you can't end to end everything.
83
You actually have to have like, I know five coders out there.
84
You guys just want it so that you can just say anything to the magic rocks and all things will be solved.
85
But that's just not it.
86
You actually have to sit down and go, what the hell am I testing?
87
What am I doing here?
88
We got to trim this back a little bit.
89
Do we really need 50 ,000 end -to -end tests for your really simple CRUD app?
90
Probably not.
91
All right, switching gears.
92
You know, kind of funny with context switching here.
93
I feel this one the most.
94
I feel this one absolutely the most because this is the one that affects me the most.
95
Now, something that I'm really good at is thinking deeply about a problem.
96
That is why I became a programmer.
97
That's why I like doing it.
98
Now, I've been able to find some joy in
99
that again in the day and age of AI by really just focusing and working through a particular problem.
100
But one of the problems about that is that AI.. is slow as hell.
101
It's like both, it's both way faster than me and also way slower than me.
102
And so you kind of get this really weird experience where you just like, you think about something for a long time,
103
you sit down, you type up some stuff.
104
And then all of a sudden, you have to wait again for like 10, 15, 20 minutes, right?
105
And so you're like, Oh, okay, well, naturally, you know what I should do?
106
I should just kick off another task.
107
You know what I mean?
108
Like, I could totally do this.
109
Like, what am I gonna do for 10 to 15 minutes?
110
And then what ends up happening, you now have like four concurrent tasks and you feel completely lost in the sauce every single time.
111
Like I can't, I can't do that.
112
I've kind of given into the fact that I'm a usually a one task kind of person.
113
Now, if I'm not necessarily looking at any of the code and I'm not trying to like really craft something, I'm just kind of blasting.
114
Okay, sure.
115
Then I can have multiple things running at one time.
116
But generally speaking, I'm kind of like a singular task individual, which is funny because if I have a feature going,
117
I can then go on to like discord slack
118
and I can actually answer some things and I can engage in
119
that kind of distraction
120
but I can't really develop two features super well simultaneously at least two may okay maybe two
121
but three I start really losing it
122
and by four I'm gone I'm not I'm not even there anymore
123
so this is more of a me personal thing
124
I try to just do like one to two tops okay I can't not a context switcher
125
so this one pisses me off so much hype FOMO dude there's
126
so many people and I've said this for years at this point.
127
When someone says, if you're not doing X, you're not going to make it.
128
I want you just to like never think about that person again.
129
Okay, you're gonna make it.
130
You know, just think about this.
131
One year ago, the way you used an agent was drastically different than the way you use it today.
132
The way you used it two years ago was so very, very different than how you used it one year ago,
133
which is so very different than how you use it today.
134
Again, this idea that if you aren't totally bought in, or if you're aren't doing this very specific thing, like if you're not Jevin,
135
if you're not figuring out your decision API framework today, then guess what?
136
You're not going to make it tomorrow.
137
It's like, bro, Jev wasn't even around two weeks ago.
138
What the hell are you talking about?
139
Having a reasonable discussion with people about AI's realistic capabilities,
140
I swear 99 % of the people you talk to are actually functionally insane when it comes to this.
141
I, like, this is not me exaggerating.
142
This is not me saying something just for the up dudes here.
143
Okay.
144
But during react Miami, okay, this was just like four months ago, five months ago, people from SF, the SF boys.
145
Okay.
146
They were utterly convinced.
147
Absolutely no change in their mind that in six months, AI would be able to create a Vercel, no problems, no mistakes, make it happen.
148
It's just like, yo, you're not creating cloudflare.
149
You're not creating Vercel just like that.
150
Right.
151
You can't be an ignoramus and be like Vercel.
152
I'm sorry.
153
That's just not how it works.
154
And there's so many people that just have this idea that it's just like an infinite God tool.
155
And it's like, no, like I hate to break this too.
156
You can do a lot more today.
157
Like even someone who is ignorant in a lot of topics can give the appearance of
158
and produce working software in some categories in which they have no knowledge of.
159
Totally reasonable, will not argue.
160
But the idea that you can make a 10 year standing resilience service
161
that serves millions of people just by telling an AI no mistakes.
162
Like, you got the brain rots are all up in there.
163
There's like Subway Surfer and Psychosis just doing some sort of weird intercourse thing making just crazy AI babies.
164
I don't even know what that means, okay?
165
I don't know what that analogy means, but you get the idea.
166
If I was Charlie, if I was Moist Critical, I'd say that's just straight shit out of a butt.
167
Which, by the way, love that phrase.
168
Makes me happy, makes me smile every single time.
169
Now, another major theme is just too much useless text too
170
much useless text too much useless text too much useless text it is
171
so true there is just so much crap
172
that it produces i got the screenshot
173
i just have to show you right here
174
it's too funny look at this i told the ai
175
i'm like okay no narrative just simply make a list of repository patterns
176
and we're gonna start building this one at a time
177
it's like sure field guide one file per topic
178
it's just like okay that's already way too much open the one
179
you need okay you did not have to say that each is facts and code.
180
Okay, again, stop it.
181
No narrative.
182
And I'm like, bro, you were, I told you no narrative.
183
And so you wrote narrative about no narrative.
184
There's few things I hate more than the useless walls of text.
185
That is in fact, these AI babies.
186
I mean, they just don't stop.
187
They just keep on making so much text.
188
And every time I'm like, don't say narrative.
189
And it's like, gotcha, boss.
190
I said in the document, no narrative.
191
While describing the thing narratively very frustrating.
192
Also just means that I waste a huge amount of time it feels like.
193
It feels like I'm just like just hotdogging myself for no reason.
194
Like I'm out there just reading a big wall of text.
195
I'm like at the end that could have been one sentence dog.
196
You wrote me 400 words to be like by the way the client interface kind of sucks right here.
197
It's like, yeah, just say that next time.
198
So if anybody knows how to fix that one, please would love it.
199
Even Grugspeak, dude, I tried Grugspeak and yes, it does reduce the amount of output, but damn, it's a Grugspeak like paragraph.
200
It's like me no understand this, this make hard.
201
I wish this was this way.
202
Decision must be had, load bearing, always.
203
Much pressure on shoulder.
204
And you're just like, dude, shut up.
205
Just say, just say the words.
206
Now, this one's probably the one that is the most kind of vocalized among everybody,
207
whether you are super pro AI or just kind of getting into AI world.
208
This one does seem to be the number one kind of complaint I've seen universally,
209
which is not feeling like I have real ownership of anything the AI outputs.
210
And for me, this was one of the hardest hurdles to get over.
211
But now I do feel like I actually have a solution to this one.
212
So this one is actually going to be me giving you advice.
213
Okay, so let me give you an example of what I've been doing is that often when I start a new project,
214
instead of just kind of vibing it up, what I do is actually think deeply about the shape of the system in what I want.
215
And then I go and I will vibe something out just really kind of feel it all
216
and really set something up and then make sure it actually works.
217
Like just sit there and iterate on it.
218
Now produces way too many tests, way too many lines of code, all this stuff.
219
But I kind of gain a whole bunch of insight into like, okay, I want, you know, I want an automation server,
220
I want to be able to spot automation clients, I want this, I want this, I want this, I want this, I want this.
221
And now I've kind of gained all that understanding.
222
And I've gained it in kind of a big way.
223
And so then I literally do a v2 of the thing and go,
224
okay, I'm now going to design this and really think about all the steps, make sure it's really classified here,
225
do the same thing for client, do the same thing.
226
And I actually build a system that I really like.
227
And often what I've been finding is that I do lines of code as a check,
228
where not in the sense that I think more lines of code is good, or less lines of code is good.
229
But in the sense that I built the same thing with the same set of features,
230
and more thoughtful and more concisely built and just really went down and actually understood everything that I was building.
231
And now it's like half as many lines of code or quarter as many lines of code.
232
Why is that?
233
Well, I thought better about my test.
234
I thought better about the shape.
235
I thought better about the actual underlying structure of each one of the components.
236
What is the components of the system?
237
And I like legitimately software developed something via an AI the second time.
238
And I've actually found this to be really nice.
239
Like right now, the project I'm working on, I've gone from 100 ,000 lines of code,
240
and I'll probably land right around 25 ,000 to 30 ,000 lines of code.
241
And for me, that's great.
242
That means I've actually thought through something, rebuilt something, actually have better database shape, better everything, because I went through it once.
243
And now the second time, it actually feels really good.
244
And by the way, this is what I'm doing for Omachi right now.
245
I'm doing the whole Omachi automation thing.
246
I'm building something called oligarchy, the oligarchy and with that, I'm building this really large kind of agentic testing framework for the OS
247
and so for me to be able to do that,
248
I need to be able to build like a really distributed way to be able to spawn all these servers
249
and everything and so I did the first one as an experiment.
250
I loved it.
251
I was able to like think about custom harnesses, how should that like really look like and everything
252
and now I'm building the second one and it is all the same features,
253
just way better thought through and way less code and that makes me happy.
254
Like I made that.
255
I actually do get some satisfaction and ownership over that because I thought through literally everything.
256
And so that's my best piece of advice to you is that don't just slop it out there.
257
Slop it to explore.
258
Like that's the greatest thing ever.
259
We used to do this, right?
260
You know, we used to do this for anyone that's a real engineer that's been doing it for a long time.
261
By the way, we're not real engineers.
262
We're actually fake engineers.
263
For anyone that's a real developer knows you always built like a prototype to go explore.
264
Now, often your boss is like, hey, nice prototype.
265
When is it going into production, buddy?
266
What would end up happening is you build this prototype and you go, oh my gosh, look at all these different things I learned.
267
Okay, now I'm building the for real one, and you build it faster and better.
268
I'm doing the same thing.
269
But now I'm just doing it with AI.
270
Honestly, this actually gives me a lot more satisfaction in what I'm building.
271
And I actually feel some real ownership.
272
All right, so the last one, the one
273
that I feel the most bad for is this right here as a junior trying to learn new things by hand,
274
but no one around me wants me to because they get instant results in fast delivery.
275
Hence, I'm unable to find the expertise in my work.
276
This, honestly, I feel like this is the worst and biggest debacle of AI itself is that for a long time,
277
everybody gave people room to grow and understand
278
because you just kind of had to like you didn't actually have a choice as a company.
279
But now that kind of has gone away because that means all the new people can be as effective as Claude.
280
And for a lot of people, this is actually a pretty good amount of effectiveness.
281
But the reality is that if you try to challenge the AI or you come up with just like a bad idea,
282
the AI doesn't go, hey, bro, I know you made this suggestion.
283
But, you know, just looking through the architecture and everything, I actually think this would be a lot better
284
if we let's talk about this for a little bit before we go through with this change.
285
No, it never does that.
286
It just hands you a thousand line PR and goes, hey, did it how you asked me to.
287
And you know, you know, since you're not familiar with the code, you made a bunch of dumb decisions that just added crap everywhere.
288
And then this is magnified tenfold because you like younger people don't even have the chance to learn what good looks like.
289
How do you even know what good looks like?
290
You don't.
291
Honestly, I feel the most for juniors
292
because you guys have by far the shortest stick in all of this because you're expected to move like a senior now,
293
now that you have a tool that produces, quote unquote, like a senior or better, but you don't get that understanding.
294
And so it's just like, man, that just feels like an impossible task.
295
And I must say to this day, I still feel the exact same way.
296
I still feel like technical knowledge is actually a really good thing.
297
Spending your time reading and trying to learn, building a prototype, thinking about all the edge cases,
298
working through every single edge case is actually a good thing.
299
Learning about mocking and then learning why you hate mocks, but then sometimes they're actually a necessary evil.
300
Learn about dependency injection, why that can solve a lot of problems and also why it's evil.
301
Like go through and just keep on learning.
302
Just try.
303
I know it's not sexy in the day and age of AI to say these things,
304
but I just don't think moving at max speed with zero learning
305
and not actually even understanding anything is gonna be good for you long -term.
306
In five years, how do you want to be building things?
307
Do you want to still just be this person that has no idea,
308
that's just being told what to do and then you just type things in and then you hope it works
309
and you build evaluations that just go, yeah, I think this works.
310
And then you hand it out and you have no idea if it's good or bad.
311
Or do you actually want to be able to see a problem go, oh yeah, we're gonna break it up like this.
312
Let's go.
313
This will be efficient.
314
This will be good.
315
This will allow us to grow in this way.
316
This will allow for these trade -offs to be made.
317
Boom.
318
Like if you want that, you gotta get after it.
319
You gotta earn it.
320
I don't see any other way than reading, hands on a keyboard and taking a little bit of time.
321
And I do just wanna throw out one more thing.
322
I know people right now keep throwing out the not going to make it side of things like oh
323
if you don't do these things you're just not going to make
324
it like just remember you have a long life ahead of you
325
and we have absolutely no idea what the future like is holding hey maybe one day cloud will be
326
so smart you never even have to think about anything you just say make it
327
and it gets the ideal server configuration the ideal client side stuff
328
it can do all the stuff it can organize all your data
329
it knows how to actually create good tables in a database doubtful
330
but nonetheless there may come a day where all technical knowledge in some sense is useless because the AIs are so powerful.
331
They can just do everything.
332
They know all the universe ever and can synthesize all experience.
333
I don't know when that day is going to happen.
334
I think the easiest way to put this is that if I were to hire somebody today,
335
would I want the person that is just a proxy that literally just says what I say,
336
we talk about it, puts what I say into code box, watch it go spinny and say merge?
337
Or do I want the person that actually thinks through problems goes, okay, I don't think we need these tests.
338
I want tests to look like this.
339
I want this.
340
I want this.
341
I want this server.
342
I want this is how it should be laid out.
343
This is what I want on the CLI.
344
This is what I want here.
345
And they actually think through all the problems.
346
Who do you think I want?
347
I want this guy 100 % of the time, just being a proxy is never a good idea.
348
Always strive to be more than just proxying information from one person to a text box.
349
All right, so there you go.
350
That's the response to all these things.
351
If you like it, press the button already.
352
The name.
353
You know what the name is.
354
In fact, PewDiePie knows what the name is.
355
Another course I did recently was the GitHub course that is hosted by another YouTuber, Primogen, which I really like.
356
This is what this man taught me, okay?
357
He taught me that.
358
A gen.
Tải Ứng Dụng
Mọi thứ bạn cần để nói trôi chảy
Chấm điểm AIChấm từng câu nói
Luyện IPAThành thạo mọi âm
Từ vựngMở rộng vốn từ
Game Từ vựngHọc qua chơi
Cùng kênh
C11
Go’s Big Mistake
Daily ConversationUniversity StudentsWorking Adults
C13
He Realized his Mistake
Daily ConversationUniversity Students
B23
People Are Mad They're Told to Learn
Business EnglishUniversity StudentsWorking Adults
B22
Maybe we were wrong
Business EnglishUniversity StudentsWorking Adults
B23
You won't fall behind
Daily ConversationWorking Adults
B23
He’s always wrong
Business EnglishDaily ConversationUniversity Students
C27
Github are you joking?
Business EnglishUniversity StudentsWorking Adults
B2Casey Muratori Judges Our Digging Games | TheStandup
Daily ConversationWorking Adults
FOR YOU
Video gợi ý
C1246 câu
Why Software Factories Fail
Daily ConversationUniversity StudentsWorking Adults
C12
182 câu
We Let $200 GPT-Pro Think for 7 Days on Unsolved Math
Daily ConversationUniversity StudentsWorking Adults
C12
223 câu
9 Insane Claude Mods I Already Can't live Without
Daily ConversationUniversity StudentsWorking Adults
C11
65 câu
Did Anthropic Kill Git?
Daily ConversationUniversity StudentsWorking Adults
C11
198 câu
Jack Dorsey’s New Dessa AI Voice Sounds Scary Human
Daily ConversationUniversity StudentsWorking Adults
C12
151 câu
We've got separation of concerns wrong
Daily ConversationUniversity StudentsWorking Adults
C111
39 câu
You Will Only Like Half of This Video
Daily ConversationUniversity StudentsWorking Adults
C1484 câu
How to Build an AI Agent for Every Part of Your Life
Daily ConversationUniversity StudentsWorking Adults
C11
623 câu
The Only SaaS Moats Left in 2026
Daily ConversationUniversity StudentsWorking Adults
C111
734 câu
實戰練英文｜再不停，人類要滅了？！黃仁勳痛批 AI 末世論，川普突然 CALL-IN 亂入，大罵這個陰謀只會讓美國輸！｜Nvidia、All-In Summit｜長文、註解、大字版、中英對照
Business EnglishDaily ConversationUniversity Students
B21
331 câu
Dear Higgsfield, I reverse engineered you in 12 hours
Daily ConversationUniversity StudentsWorking Adults
Từ vựng và ghi chú luyện nói cho bài học này
Bài luyện nói này dựa trên video “It’s not just you”. Video này có 358 câu và 3941 từ để luyện shadowing. Phần lời nói dài 18:39. Người nói nói nhanh, khoảng 211 từ mỗi phút, nên sẽ có nhiều chỗ nối âm và nuốt âm. 85% số từ nằm trong 3.000 từ tiếng Anh thông dụng nhất; phần còn lại nên xem trước khi luyện.
Từ vựng quan trọng trong video
15 từ đáng học trong video, kèm phiên âm và nghĩa:
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| narrative danh từ | /ˈnæɹ.ə.tɪv/ | kể chuyện, tường thuật |
| server danh từ | /ˈsɝvɚ/ | trình chủ, máy chủ |
| prototype danh từ | /ˈpɹəʊtətaɪp/ | nguyên mẫu |
| sexy tính từ | /ˈsɛksi/ | quyến rũ, cuốn hút |
| suck động từ | /sʌk/ | bú |
| automation danh từ | /ˌɔ.təˈmeɪ.ʃən/ | sự tự động hóa |
| topic danh từ | /ˈtɑpɪk/ | chủ đề |
| output danh từ | /ˈaʊtpʊt/ | đầu ra |
| solve động từ | /sɒlv/ | giải quyết |
| component danh từ | /kəmˈpoʊ.nənt/ | bộ phận |
| database danh từ | /ˈdeɪtəˌbeɪs/ | cơ sở dữ liệu, CSDL |
| explore động từ | /ɪkˈsploɹ/ | thám hiểm |
| satisfaction danh từ | /sætɪsˈfækʃən/ | sự thỏa mãn |
| vibe danh từ | /vaɪb/ | cảm giác |
| programmer danh từ | /ˈpɹoʊɡɹæmɚ/ | lập trình viên |
Cụm động từ bạn sẽ nghe
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| sit down động từ | ngồi xuống, ngồi | |
| come back động từ | trở lại, trở về | |
| shut up | /ʃʌt ʌp/ | câm, câm mồm |
Những câu đáng luyện lại
Các câu ngắn, trọn ý trong video mà bạn có thể dùng lại khi giao tiếp hằng ngày:
- Jippity, did you make the website better?
- Can I pull this hat off?
- Are you tired of your agents gaslighting you?
- What am I doing here?
- You know what I mean?
Ngữ pháp trong video
Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:
| Cấu trúc | Trong video |
|---|---|
| Thì hiện tại hoàn thành tiếp diễn have/has been + -ing — việc bắt đầu từ trước và vẫn đang tiếp tục | I've been struggling · I've been doing · I've been finding |
| “Used to” used to + động từ — thói quen hoặc tình trạng trong quá khứ nay không còn | used to do |
| Thì hiện tại hoàn thành have/has + quá khứ phân từ — việc đã xảy ra nhưng còn liên quan đến hiện tại | I've made · you've been told · I've never been |
| Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làm | being locked · being changed · you've been told |
Phát âm cần chú ý
Người nói dùng 111 dạng rút gọn, ví dụ I'm, I've, you're. Hãy nói theo dạng ngắn đúng như bạn nghe.
- Âm “th”: nonetheless /ˌnʌnðəˈlɛs/, altogether /ɔl.tuˈɡɛð.ɚ/, thoughtful /ˈθɔːtfəl/, synthesize /ˈsɪnθəsaɪz/
- Âm “sh” và “zh”: ownership /ˈoʊnɚʃɪp/, automation /ˌɔ.təˈmeɪ.ʃən/, satisfaction /sætɪsˈfækʃən/, gosh /ɡɑːʃ/, efficient /ɪˈfɪʃənt/
- Từ dài — đặt trọng âm cho đúng: automation /ˌɔ.təˈmeɪ.ʃən/, satisfaction /sætɪsˈfækʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, necessarily /ˌnɛs.əˈsɛɹ.ə.li/, architecture /ˈɑː.kɪˌtɛk.t͡ʃə/
Những âm người Việt thường gặp khó:
- Cụm phụ âm cuối — đọc đủ từng âm, đừng nuốt âm cuối: solve /sɒlv/, component /kəmˈpoʊ.nənt/, efficient /ɪˈfɪʃənt/, experiment /ɪkˈspɛɹ.ə.mənt/, hence /ˈhɛns/
- Âm /tʃ/, /dʒ/ và /ʒ/ — tiếng Việt không có, đừng đọc thành “ch” hay “gi”: naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, engage /ɪnˈɡeɪd͡ʒ/, genius /ˈd͡ʒin.jəs/, suggestion /səˈd͡ʒɛst.ʃən/
- Âm /æ/ — mở miệng rộng hơn âm “e”: narrative /ˈnæɹ.ə.tɪv/, satisfaction /sætɪsˈfækʃən/, programmer /ˈpɹoʊɡɹæmɚ/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, blast /blæst/
Cách luyện với video này
- Nghe hết video một lần, chưa cần nói, và ghi lại những từ bạn chưa biết.
- Bắt đầu ở tốc độ 0,75×, nói đuổi từng câu, rồi quay lại tốc độ bình thường khi đã quen.
- Ghi âm giọng mình rồi so với bản gốc, chú ý các từ như narrative, server, prototype.
Phương Pháp Shadowing Là Gì?
Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.